The HiBench benchmark suite: Characterization of the MapReduce-based data analysis

Shengsheng Huang, Jie Huang, J. Dai, T. Xie, Bo Huang
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引用次数: 748

Abstract

The MapReduce model is becoming prominent for the large-scale data analysis in the cloud. In this paper, we present the benchmarking, evaluation and characterization of Hadoop, an open-source implementation of MapReduce. We first introduce HiBench, a new benchmark suite for Hadoop. It consists of a set of Hadoop programs, including both synthetic micro-benchmarks and real-world Hadoop applications. We then evaluate and characterize the Hadoop framework using HiBench, in terms of speed (i.e., job running time), throughput (i.e., the number of tasks completed per minute), HDFS bandwidth, system resource (e.g., CPU, memory and I/O) utilizations, and data access patterns.
HiBench基准测试套件:基于mapreduce的数据分析的特征
MapReduce模型在云中的大规模数据分析中变得越来越突出。在本文中,我们提出了对Hadoop的基准测试,评估和表征,Hadoop是MapReduce的开源实现。我们首先介绍HiBench,一个新的Hadoop基准测试套件。它由一组Hadoop程序组成,包括合成微基准测试和真实的Hadoop应用程序。然后,我们使用HiBench来评估和描述Hadoop框架,包括速度(即作业运行时间)、吞吐量(即每分钟完成的任务数量)、HDFS带宽、系统资源(例如CPU、内存和I/O)利用率和数据访问模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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